Clinical predictive value of the age, creatinine, and ejection fraction score in patients in acute type A aortic dissection after total arch replacement

The age, creatinine, and ejection fraction (ACEF) score has been accepted as a predictor of poor outcome in elective operations. This study aimed to investigate the predictive value of ACEF score in acute type A aortic dissection (AAAD) patients after total arch replacement. A total of 227 AAAD patients from July 2021 and June 2022 were enrolled and divided into Tertiles 1 (ACEF ≤ 0.73), Tertiles 2 (0.73 < ACEF ≤ 0.95), and Tertiles 3 (ACEF > 0.95). Using inverse probability processing weighting (IPTW) to balance the baseline characteristics and compare the outcomes. Cox logistic regression was used to further evaluate the survival prediction ability of ACEF score. The in-hospital mortality was 9.8%. After IPTW, in the baseline characteristics reached an equilibrium, a higher ACEF score before operation still associated with higher in-hospital mortality. After 1 year follow-up, 184 patients (90.6%) survival. Multivariable analysis revealed that ACEF score (adjusted hazard ratio  1.68; 95% confidence interval 1.34–4.91; p = 0.036) and binary ACEF score (adjusted HR 2.26; 95% CI 1.82–6.20; p < 0.001) was independently associated with 1-year survival. In addition, net reclassification improvement (NRI) and integrated differentiation improvement (IDI) verified that the ACEF score and binary ACEF score is an accurate predictive tool in clinical settings. In conclusions, ACEF score could be considered as a useful tool to risk stratification in patients with AAAD before operation in daily clinical work.

have been proposed.Of those, the European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) 3 , and the German Registry for Acute Aortic Dissection Type A (GERAADA) score 4 are the best known.The GERAADA score, which is specifically designed for predicting 30-day mortality in patients undergoing surgery for AAAD, contains a majority of the risk factors implemented in the EuroSCORE II 5 .The age, creatinine, and ejection fraction (ACEF) score is a novel and simple risk assessment tool which includes only three variables, initially developed in the prediction of mortality in patients undergoing elective cardiac operations 6 .And further independent validated in several types of cardiovascular surgery, such as valve surgery and ventricular reconstruction [7][8][9] .However, data on the ACEF score in patients with AAAD are scarce.Consequently, the present study was conducted to assess the predictive value of the ACEF score in patients with AAAD after total arch replacement.

Patient population
This was a retrospective, single-center observational study of patients with AAAD underwent total arch replacement in our institution between July 2021 and June 2022.The diagnosis was made according to computed tomography angiography (CTA) and echocardiography.All the patients met the indications for total arch replacement which was described in our previous study 10 .The exclusion criteria were as follows: (1) less than 18 years; (2) sub-acute and chronic AD (the diagnosis was made according to onset time and imaging 11 ); (3) absence of crucial clinical data (required to calculate the ACEF I or II were missing).Figure 1 provides an overview of the study procedures.
The present study was following the guidelines of the Declaration of Helsinki and was approved by the Medical Ethics Committee of Fujian Medical University Union Hospital.This retrospective study had the approval from the ethics committee, with the need for informed consent from patients was waived.

Data collection and calculation
The patients were divided into three groups separated by the 33rd and 67th percentiles (tertiles) of ACEF score.Clinical data were collected from electronic medical records by one researcher and checked by another researcher randomly.Preoperative imaging examinations and laboratory tests were performed at emergency admission before any treatment.All in-hospital survival patients were followed up via outpatient clinic visits or telephone interviews after discharge.The follow-up data, including follow-up time and status, was collected.

Endpoints
For the purposes of the present study, the primary endpoint was all-cause mortality.The secondary outcome was severe postoperative complications, defined by The International Aortic Arch Surgery Study Group (IAASSG) 13 , requiring intervention under regional or general anesthesia or requiring new ICU admission or ongoing ICU management for > 7 d or hospitalization for > 30 d, or causing secondary organ failure 14 .

Ethics approval
The present study was following the guidelines of the Declaration of Helsinki and was approved by the Medical Ethics Committee of Fujian Medical University Union Hospital.

Patient consent
This retrospective study had the approval from the ethics committee of Fujian Medical University Union Hospital, with the need for informed consent from patients was waived.

Baseline characteristics
We totally enrolled 227 patients who had undergone total arch replacement.2 patients were excluded for missing key data.After exclusions, a total of 225 AAAD patients for further analysis.The median age was 51.24 ± 11.43 years, with 131 (58.22%) males and 94 (41.78%) females.Patients were classified into three groups according to the tertiles of ACEF score: Tertiles 1 (ACEF ≤ 0.73, n = 73), Tertiles 2 (0.73 < ACEF ≤ 0.95, n = 78) and Tertiles 3 (ACEF > 0.95, n = 74).Obviously, significant differences were observed among tertiles in age, serum creatinine and LVEF.In addition, patients with a high ACEF score had a higher proportion of hypertension (p = 0.027) and more likely to receive a simpler root procedure (p = 0.003).In order to make all the data comparable, the IPTW was conducted to match the baseline and surgical variables aside from age, serum creatinine, LVEF.After matching, no else significant differences were detected.Table 1 Summarizes the baseline characteristics comparison between groups before and after IPTW (Fig. 2).The standardized mean differences were assessed graphically by using a Love plot.All covariates that had a standardized mean difference of < 0.25 were determined to be balanced.

Perioperative outcomes
In-hospital death occurred in 22 patients (2 in Tertiles 1, 5 in Tertiles 2, 15 in Tertiles 3, respectively) and the mortality rate was 9.8% (2.74% vs. 6.41% vs. 20.27%,p = 0.001).This difference also remained statistically significant (p = 0.024) after IPTW weighting.Before IPTW, A higher incidence of renal failure in patients with a high ACEF score was observed (16.44% vs. 24.36% vs. 41.89%,p = 0.002), however this effect was no longer found after weighting (p = 0.777).There was a statistically significant difference in hepatic insufficiency among groups (p = 0.035) after IPTW, while it was not apparent before IPTW.No significant differences were observed in the rest complications after IPTW.The comparison of perioperative outcomes between the groups before and after matching is summarized in Table 2.In ROC curve analysis, the discriminative capacity of the ACEF score was better than ACEF II score in predicting in-hospital mortality (Fig. 4a).The AUC of ACEF, ACEF II score was 0.723 (95% CI 0.613-0.833;p = 0.006), 0.642 (95% CI 0.512-0.771;p = 0.029), respectively.But there is no significant difference (p = 0.127).

Clinical application of ACEF score
A prediction model was constructed from baseline factors including BMI, cerebral malperfusion, dissection involving supra-aortic vessels, the addition of continuous ACEF score or binary ACEF score (transformed to a categorical variable based on the cut-off value generated by ROC analysis) improve Harrell's C-index for 1-year mortality (0.877 and 0.879).However, the time dependent NRI and IDI tended both to be improved in binary ACEF score model (0.435, p < 0.001, and 0.131, p < 0.001), respectively (Table 4).The time-dependent AUC (Fig. 4c) shows that the AUC of binary ACEF score model continues to increase within 1 year postoperatively (3, 6, 12 month: 0.876, 0.892, 0.904).

Discussion
The current investigation showed that the predictive value of the ACEF score in early surgical outcome in AAAD patients underwent total arch replacement.Patients in a higher ACEF score possibly indicating a poor baseline characteristic, with more comorbidities and prior significant medical history.This lack of consistency made direct comparison difficult between groups.Thus, we applying the IPTW to balance the baseline and surgical variables without reducing the sample size, making the conclusion more persuasive and scientific.The key advantage of ACEF score is its simplicity and rapidity, no specific software is necessary.The ACEF score could be considered as a useful tool to risk stratification in patients with AAAD before operation in daily clinical work.Acute type A aortic dissection (AAAD) is a life-threatening pathology.The mortality is reportedly 9.4-22% 1, 16 .Despite the advances in surgical techniques and perioperative care, the short-term outcome is still undesirable with in-hospital mortality at 9.8% and 1-year survival at 90.6%.Previous studies suggested that the AAAD surgical outcome was closely related to preoperative state 17 .However, a comprehensive evaluation within the limited time is admittedly a challenging task.Therefore, it is necessary to find a rapid and easy method to identify highrisk patients.Then, a comprehensive baseline data evaluation of high-risk patients should be taken to developing an optimize treatment strategies.Currently, ACEF score has been considered as a useful risk stratification tool in many cardiovascular disease patients [18][19][20] .The advanced age, high level of serum creatinine and the worse cardiac function has also been acknowledged as the important independent predictive factor for AAAD patients [21][22][23] .In our study, by comparing AAAD patients in different ACEF score, although the baseline has been balanced, a higher ACEF score was strongly associated with a higher in-hospital mortality.In all discharged patients, the 1-year survival still affected by a low baseline ACEF score.
The ACEF score, comprising only three key variables, is undoubtedly not a substitute for well-recognized scores such as the EuroSCORE II and the GERAADA score in the assessment model for Stanford type A acute aortic dissection.It cannot accurately calculate surgical mortality.Its significance lies particularly in the quick and effective identification of high-risk patients.This provides a reference for optimizing clinical decision-making in high-risk patients, including further comprehensive assessment, more aggressive use of support devices, simplified surgical procedures, and close postoperative monitoring.In the meantime, ACEF score also has a certain predictive role in the 1-year outcomes of AAAD patients.For patients in high ACEF score, intensive follow-up, and guidance in early postoperative are necessary.

Table 2.
Comparisons of perioperative outcomes according to ACEF score groups after before matching and after IPTW.Values are given as numbers or numbers and percentages.In-hospital mortality, death within the same hospital admission or death from any-cause 30-day post-procedure.Permanent neurological deficits, stroke with positive neuroimaging findings.Low cardiac output syndrome, patients requiring intra-aortic balloon pump insertion.Cardiogenic shock, persistent hypotension (systolic blood pressure < 90 mmHg) with the cardiac index (CI) < 1.8 L/(min•m 2 ).Secondary intubation, patients requiring re-intubation because of respiratory failure.Tracheotomy, patients requiring tracheostomy for long-term ventilator dependence.Renal failure, serum creatinine increased by > 3 times the baseline values, GFR decreased by > 75%, oliguria: urine output < 0.3 mL•kg −1 •h −1 for 24 h, or anuria > 12 h or requiring temporary hemodialysis support for resolution.Hepatic insufficiency, hepatobiliary ischemia manifested as metabolic acidosis or increased lactate or prothrombin time, requiring general surgeon consultation.Sepsis, a severe infection accompanied by symptoms and signs of a primary infectious focus, and positive blood culture results for bacteria.Gastrointestinal bleeding, patients with evidence of gastrointestinal bleeding, accompanied by a significant progressive decrease in hemoglobin.Re-operation, patients requiring re-operation on in the immediate postoperative period because of bleeding.Sternal wound infection, deep wound infection involving the sternum, requiring surgical intervention under general anesthesia, or wound dehiscence requiring reapproximation of the sternum under general anesthesia.The ACEF II score, a modified version of the ACEF score that includes the variables emergency surgery and preoperative anemia, is already being widely used 24 .There is no doubt that emergency surgery and preoperative anemia are both risk factors of thoracic aortic surgery.In the current study, however, ACEF II score did not show a good prediction ability for in-hospital mortality and 1-year survival in AAAD patients underwent total arch replacement.One reason for this might be the vast majority of the AAAD patients (88.00%) underwent emergency surgery and the assignment value of emergency surgery in ACEF II score was much high (3 (if emergency surgery)).It may lead to the overestimation of actual mortality rate.Hence, for better prediction of mortality in AAAD patients, the equations of ACEF II scores should be recalibrated.
It is strange that renal failure is no more a significant variable between groups after weighing the baseline and surgical variables.In the current study, concomitant chronic renal disease is the main cause of the preoperative elevated creatinine level.We can only speculate that postoperative acute renal failure is considerably more often caused by acute ischemia.

Figure 1 .
Figure 1.The flowchart of patient selection and analysis.

Figure 2 .
Figure 2. A Love plot was used to assessed standardized mean differences before adjusting and after adjusting.

Figure 4 .
Figure 4. ROC curves of ACEF score and ACEF IIin predicting in-hospital (a) ROC curves of ACEF score in predicting in-hospital at different time (b) Time-dependent ROC curve of binary ACEF model (c).
15e statistical analysis was conducted in R software version 4.3.2.Continuous variables were reported as mean ± SD or median and quartile range, and compared using analysis of variance or Mann-Whitney test.Categorical variables were expressed as percentages and compared by chi-square analysis.To ensure balance in baseline characteristic, inverse probability of treatment weighting (IPTW) was utilized.Compared to propensity score matching (PSM), IPTW can minimize the influence of confounding variables while maximizing the amount of available information.The sample size formed after IPTW is based on the weight and the pseudo sample size generated by the actual sample15.Discrimination performance of ACEF, ACEF II score in predicting mortality Vol.:(0123456789) Scientific Reports | (2024) 14:10776 | https://doi.org/10.1038/s41598-024-58608-4www.nature.com/scientificreports/Statistical analysis

Table 3 .
Cox regression analyses for 1-year outcomes according to ACEF score groups.Values are given as numbers or numbers and percentages.CABG, coronary artery bypass grafting; CPB, cardiopulmonary bypass; ACC, aortic cross-clamp.

Table 4 .
Predictive accuracy of the ACEF score using Harrell's C-index for Cox hazard model, time dependent NRI and time dependent IDI.Values are given as numbers or numbers and percentages.NRI, net reclassification improvement; IDI, integrated discrimination improvement.